Application of Pizza Sales Data Mining Using Apriori Method

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Rusdiansyah Rusdiansyah Nining suharyanti Triningsih Triningsih Murniyati Murniyati
Corresponding Author:
Rusdiansyah Rusdiansyah | rusdirds@gmail.com

Copyright (C):
Rusdiansyah Rusdiansyah, Nining suharyanti, Triningsih Triningsih, Murniyati Murniyati

Abstract

Pizza is a processed food originating from Italy and has been spread in various other countries including one of them in Indonesia. Pizza is a processed food that is currently sought after by various groups of people so as to make the pizza business opportunity very profitable, if it is run in a food business. Currently the pizza business has very favorable prospects when compared to other businesses. Moreover, the targeted target can be from all walks of life from children to adults. Pizza sales transactions that produce sales data every day, have not been able to maximize the use of sales data. Sales data is only stored as an archive, so it becomes a pile of data. Therefore the use of data mining is used to solve this problem. A priori algorithm is a data mining method by using minimum support parameters, minimum confidence and will analyze in the period of every month of sales transactions. This study produces data on the results of the process of association rules from the data collection of sales transactions. From the association rules it can be concluded that the pattern of pizza sales, where consumers more often buy Meatzza and Cheese Mania, as evidenced by the results of calculations using Apriori Algorithm and Rapidminer 5.3, with support of 30% and 60% confidence.

Keyword: Pizza Sales, Apriori Algorithms, Association Rule

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How to Cite
RUSDIANSYAH, Rusdiansyah et al. Application of Pizza Sales Data Mining Using Apriori Method. SinkrOn, [S.l.], v. 4, n. 2, p. 1-5, mar. 2020. ISSN 2541-2019. Available at: <http://jurnal.polgan.ac.id/index.php/sinkron/article/view/10500>. Date accessed: 26 may 2020. doi: https://doi.org/10.33395/sinkron.v4i2.10500.
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